Table 1.

Accuracy, precision, and recall performance in detecting AdV-C2- and HSV-1-infected cells by ViResNet compared to k-NN, SVM, and decision tree methods

	$\mathrm{A}\mathrm{c}\mathrm{c}\mathrm{u}\mathrm{r}\mathrm{a}\mathrm{c}\mathrm{y}=\frac{\mathrm{T}\mathrm{P}+\mathrm{T}\mathrm{N}}{\mathrm{T}\mathrm{P}+\mathrm{T}\mathrm{N}+\mathrm{F}\mathrm{P}+\mathrm{F}\mathrm{N}}$	$\mathrm{P}\mathrm{r}\mathrm{e}\mathrm{c}\mathrm{i}\mathrm{s}\mathrm{i}\mathrm{o}\mathrm{n}=\frac{\mathrm{T}\mathrm{P}}{\mathrm{T}\mathrm{P}+\mathrm{F}\mathrm{P}}$	$\mathrm{R}\mathrm{e}\mathrm{c}\mathrm{a}\mathrm{l}\mathrm{l}=\frac{\mathrm{T}\mathrm{P}}{\mathrm{T}\mathrm{P}+\mathrm{F}\mathrm{N}}$
AdV-C2:
ViResNet	0.95	0.94	0.92
k-NN	0.64	0.62	0.61
SVM	0.63	0.63	0.58
Decision tree	0.64	0.62	0.59
HSV-1:
ViResNet	0.94	0.92	0.93
k-NN	0.64	0.61	0.56
SVM	0.61	0.58	0.59
Decision tree	0.65	0.62	0.61

TP, TN, FP, and FN denote true positives, true negatives, false positives, and false negatives of the predictions on the test data set correspondingly.